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Record W2612241764

Jordanian Household Socioeconomic Conditions and Child Health

2017· article· en· W2612241764 on OpenAlexaboutno aff
Mahmoud Hailat

Bibliographic record

VenueJordan journal of economic sciences · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsBirth orderSocioeconomic statusOddsDemographyQuarter (Canadian coin)Logistic regressionChild healthChild mortalityOdds ratioMedicinePopulationPediatricsGeographySociology
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the effect of Jordanian household circumstances on child health. The main objective is to figure out the extent to which household circumstances matter for child survival and health of surviving children. Repeated cross sectional micro-data from the Demographic and Health Surveys (DHS) for Jordan spanning the period 1997–2009 is used. Logit models and standard linear regression models are employed in the analysis. Main findings may be summarized as follows. Household conditions appear to matter for child survival odds and health of surviving children. Boys’ survival odds ratio is about quarter to one-third less than girls. However, surviving boys are on average taller than girls. Chances of surviving increases with child birth order, whereas birth order is negatively associated with height of survivors. Education of the mother enhances the chances of child surviving by 60-120%, and increases the child height. Given age, effects of mother education is more significant for boys compared to girls. Physician care during conception is positively associated with the health of survivors. Ownership of refrigerator is positively associated with child height. Finally, children in urban areas show better health compared to their counterparts in rural areas.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.101
GPT teacher head0.461
Teacher spread0.361 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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